Abstract
Agents in a multiagent system may in many cases find themselves in situations where inconsistencies arise. In order to properly deal with these, a good belief revision procedure is required. This paper illustrates the usefulness of such a procedure: a certain belief revision algorithm is considered in order to deal with inconsistencies and, particularly, the issue of inconsistencies, and belief revision is examined in relation to the GOAL agent programming language.
Highlights
When designing artificial intelligence, it is desirable to mimic the human way of reasoning as closely as possible to obtain a realistic intelligence albeit still artificial
This paper illustrates the usefulness of such a procedure: a certain belief revision algorithm is considered in order to deal with inconsistencies and, the issue of inconsistencies, and belief revision is examined in relation to the GOAL agent programming language
A particular algorithm for belief revision has been considered. It has the advantages of being efficient and straightforward to implement; it has the disadvantages that it is only defined for a weak logic of the agent and that it requires the nontrivial question of a preference ordering
Summary
It is desirable to mimic the human way of reasoning as closely as possible to obtain a realistic intelligence albeit still artificial. This includes the ability to construct a plan for solving a given problem and to be able to adapt the plan or discard it in favor of a new. In these situations the environment in which the agents act should be considered as dynamic and complicated as the world it is representing. The belief revision algorithm used in this paper will be compared to other approaches dealing with inconsistency
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